CN109191543A - A kind of AC sampling is the same as profile data generation method - Google Patents
A kind of AC sampling is the same as profile data generation method Download PDFInfo
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Abstract
The present invention provides a kind of AC sampling with profile data generation method, is related to power system automation technology field.This method first using the real time electrical quantity data of different acquisition device acquisition power grids, classify according to different frequencies by the real time electrical quantity data of same acquisition device acquisition；The three parametric sinusoidal wave profile fitting algorithm of data application under same frequency that same acquisition device acquires is fitted again, obtains the piecewise fitting function for acquiring data under different frequency；Then it determines a time reference point, and the time at find out different frequency on a timeline similarly hereinafter time point, and the time found out is brought into obtained piecewise fitting function, the corresponding data value at section time point of seeking common ground；The data of all same sections found out are finally formed into same profile data in data display platform.For AC sampling provided by the invention with profile data generation method, the same profile data error of generation is small, and precision is high, can analyze for advanced applied software and provide more accurate data.
Description
Technical field
The present invention relates to power system automation technology fields more particularly to a kind of AC sampling with profile data generation side
Method.
Background technique
Currently, with the continuous development of modern science and technology level, electronics technology sector such as radar, communication, medical treatment, instrument etc.
All reach a new height, it is higher and higher to the required precision of data, it is also more and more intelligent inside power grid, it is deposited in power grid
In many advanced applied softwares, accurate data can make advanced applied software make reasonable decision, but present power measurement
Real data be non-same profile data, this data error is larger, affects the analytical effect of all kinds of advanced applied softwares, works as electricity
After net breaks down, it is unfavorable for making correct decision, is unfavorable for power network safety operation, accordingly, it is desirable to provide power grid is same
Profile data provides accurate data for application software analysis.
Least square method is used widely in terms of solving acquisition data processing and error, and data processing can be improved
Efficiency and accuracy, it has also become important, the reliable technological means of data processing.According to the n of two variables x and y
Group experimental data, (xi, yi), i=1,2 ..., n acquire the approximate expression (empirical equation) of the functional relation of the two variables, this
A process is exactly curve matching.After having selected the mathematical formulae model of curve, least square method trade-off curve equation is used
In coefficient, partial derivative is generally asked to each coefficient by the quadratic sum to deviation, makes partial derivative zero to establish equation group, warp
A series of derivations are crossed, coefficient formula is obtained, then acquires coefficient.The equidistant sample sequence of sinusoidal waveform obtains thirdly parameter is quasi-
Sinusoidal function is closed, is a kind of baseband signal processing method, is applied in many situations, such as evaluates data acquisition system
Number of significant digit, acquisition rate, ac gain, interchannel delay, trigger characteristic of system etc., modulated signal digital demodulation and
Also there is application in distortion measurement.
For three parametric sinusoidal wave profile fitting algorithms, has numerous scholars and made a lot of research work, for this kind of calculation
Method, relative accuracy, absolute precision, efficiency, convergence and runing time etc. can satisfy the requirement of engineer application substantially.
Summary of the invention
In view of the drawbacks of the prior art, the present invention provides a kind of AC sampling with profile data generation method, realizes acquisition
Electric network data same profile data generation, for advanced applied software analysis complete data are provided.
A kind of AC sampling is the same as profile data generation method, comprising the following steps:
Step 1, the real time electrical quantity data that power grid is acquired using acquisition device different in power grid, and to same acquisition device
The electricity data of acquisition is fitted on different tones；
The electricity data to the acquisition of same acquisition device is fitted on different tones method particularly includes:
Step 1.1 acquires different frequency (f using the acquisition device in power grid1, f2, f3... ... fm) under power grid it is real-time
Electricity data, and data collected are classified according to different frequencies；Obtain the real-time electricity of same acquisition device acquisition
Measure data are as follows: [(t1,1, y1,1)、(t1,2, y1,2)、……(t1, n, y1, n)]、[(t2,1, y2,1)、(t2,2, y2,2)、……(t2, n,
y2, n)]、……[(tR, 1, yR, 1)……(tR, i, yR, i)……(tR, n, yR, n)]……[(tM-1,1, yM-1,1)、(tM-1,2,
yM-1,2)、……(tM-1, n, yM-1, n)]、[(tM, 1, yM, 1)、(tM, 2, yMm, 2)、……(tM, n, yM, n)]；
Wherein, tR, iFor frequency frWhen, the time of i-th of electricity data of acquisition；yR, iFor frequency frWhen, i-th of acquisition
Electricity data, i=1,2 ..., n, n is the power grid real time electrical quantity data of same acquisition device acquisition in power grid, r=1,2 ...,
M, m are different total number of frequencies；
Power grid real time electrical quantity data [(t under step 1.2, the same frequency for acquiring acquisition device same in power gridR, 1,
yR, 1)……(tR, i, yR, i)……(tR, n, yR, n)] be fitted with three parametric sinusoidal wave profile fitting algorithms, specific method
Are as follows:
Step 1.2.1, seek common ground an acquisition device frequency be frWhen sampling period；
The sampling rate of known acquisition device is vr, the sampling interval is Δ tr, number of samples n, then each sampling period
Angular frequency is
Step 1.2.2, it seeks common ground the matched curve of electricity data that an acquisition device acquires under same sample frequency；
The data sequence that same acquisition device acquires under same sample frequency is (tR, 1, yR, 1)……(tR, i,
yR, i)……(tR, n, yR, n), then the sinusoidal discrete form of the data acquired are as follows:
yR, i=Brsin(ωrtR, i)+Crcos(ωrtR, i) (2)
Wherein, BrAnd CrFor equal coefficient；
Choose BrAnd Cr, keep residual sum of squares (RSS) shown in following formula minimum:
Coefficient B at this timer=Br0And Cr0Least square fitting value for the electricity data acquired under same frequency；
Step 1.2.3, the described selection BrAnd Cr, keep residual sum of squares (RSS) the smallest method particularly includes:
Construct following matrix:
It is then matrix form by residual sum of squares (RSS) simplification of a formula, shown in following formula:
WhenWhen minimum, unknown θ is obtainedrLeast square solutionShown in following formula:
Shown in the following formula of the fitting function of the electricity data then acquired under same frequency:
The amplitude A in the optimum fit curve of trigonometric function is found out according to fitting functionrWith phase angle αr, shown in following formula:
And then the functional relation of the electricity data of r-th of period acquisition of same acquisition device is obtained, shown in following formula:
g(tr)=Arsin(ωrtr+αr)
Step 1.3 repeats step 1.2, obtains the piecewise fitting function that data are acquired under same acquisition device different frequency,
g(t1), g (t2) ..., g (tm)；
Step 2 determines that power grid needs to be sought the same profile data at moment；
Step 2.1 determines a time reference point, and find out different frequency on a timeline similarly hereinafter a time point when
Between；
If with frequency f1Take t in the data period a little1For the benchmark time, then with frequency frThe correspondence time a little is taken in period
Shown in the following formula of point:
Step 2.2, the time that step 2.1 is found out are brought by the expression formula of the obtained piecewise fitting function of step 1.3
In, the corresponding data value at section time point of seeking common ground, shown in following formula:
g(tr)=Arsin(ωrtr+αr)
Step 2.3 repeats step 2.2, calculates r=1, g (t when 2,3 ..., mr), and then find out the number of all same sections
According to；
Step 3: the data of all same sections found out are formed into same profile data in data display platform.
As shown from the above technical solution, the beneficial effects of the present invention are: a kind of AC sampling provided by the invention is the same as disconnected
Face data generation method breaks through traditional power measurement data analysing method, using data point has been acquired, is intended by algorithm
It closes, is fitted optimal mathematic curve, with the mathematic curve asked, determine the data of synchronization at different frequencies, realize
The same section of electric network data acquires, and provides complete data for advanced applied software analysis.The same section that the method for the present invention generates
Data error is small, and precision is high, can analyze for advanced applied software and provide more accurate data.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the AC sampling provided in an embodiment of the present invention with profile data generation method；
Fig. 2 is that the power grid in power grid provided in an embodiment of the present invention under the different frequency of same acquisition device acquisition is electric in real time
Measure the schematic diagram of data；
Fig. 3 is the fitting for the data that same acquisition device acquires at different frequencies in power grid provided in an embodiment of the present invention
Curve synoptic diagram；
Fig. 4 is the same profile data schematic diagram that same acquisition device generates in power grid provided in an embodiment of the present invention.
Specific embodiment
With reference to the accompanying drawings and examples, specific embodiments of the present invention will be described in further detail.Implement below
Example is not intended to limit the scope of the invention for illustrating the present invention.
The present embodiment is by taking certain power grid as an example, using AC sampling of the invention with profile data generation method, by the power grid
Real-time measuring data generate same profile data.
A kind of AC sampling is with profile data generation method, as shown in Figure 1, comprising the following steps:
Step 1, the real time electrical quantity data that power grid is acquired using acquisition device different in power grid, and to same acquisition device
The electricity data of acquisition is fitted on different tones；
The electricity data to the acquisition of same acquisition device is fitted on different tones method particularly includes:
Step 1.1 acquires different frequency (f using the acquisition device in power grid1, f2, f3... ... fm) under power grid it is real-time
Electricity data, and data collected are classified according to different frequencies, as shown in Figure 2；Same acquisition device is obtained to adopt
The real time electrical quantity data of collection are as follows: [(t1,1, y1,1)、(t1,2, y1,2)、……(t1, n, y1, n)]、[(t2,1, y2,1)、(t2,2,
y2,2)、……(t2, n, y2, n)]、……[(tR, 1, yR, 1)……(tR, i, yR, i)……(tR, n, yR, n)]……[(tM-1,1,
yM-1,1)、(tM-1,2, yM-1,2)、……(tM-1, n, yM-1, n)]、[(tM, 1, yM, 1)、(tM, 2, yM, 2)、……(tM, n, yM, n)]；
Wherein, tR, iFor frequency frWhen, the time of i-th of electricity data of acquisition；yR, iFor frequency frWhen, i-th of acquisition
Electricity data, i=1,2 ..., n, n is the power grid real time electrical quantity data of same acquisition device acquisition in power grid, r=1,2 ...,
M, m are different total number of frequencies；
Power grid real time electrical quantity data [(t under step 1.2, the same frequency for acquiring acquisition device same in power gridR, 1,
yR, 1)……(tR, i, yR, i)……(tR, n, yR, n)] be fitted with three parametric sinusoidal wave profile fitting algorithms, specific method
Are as follows:
Step 1.2.1, seek common ground an acquisition device frequency be frWhen sampling period；
The sampling rate of known acquisition device is vr, the sampling interval is Δ tr, number of samples n, then each sampling period
Angular frequency is
Step 1.2.2, it seeks common ground the matched curve of electricity data that an acquisition device acquires under same sample frequency；
The data sequence that same acquisition device acquires under same sample frequency is (tR, 1, yR, 1)……(tR, i,
yR, i)……(tR, n, yR, n), then the sinusoidal discrete form of the data acquired are as follows:
yR, i=Brsin(ωrtR, i)+Crcos(ωrtR, i) (2)
Wherein, BrAnd CrFor equal coefficient；
Choose BrAnd Cr, keep residual sum of squares (RSS) shown in following formula minimum:
Coefficient B at this timer=Br0And Cr0Least square fitting value for the electricity data acquired under same frequency；
Step 1.2.3, the described selection BrAnd Cr, keep residual sum of squares (RSS) the smallest method particularly includes:
Construct following matrix:
It is then matrix form by residual sum of squares (RSS) simplification of a formula, shown in following formula:
WhenWhen minimum, unknown θ is obtainedrLeast square solutionShown in following formula:
Shown in the following formula of the fitting function of the electricity data then acquired under same frequency:
The amplitude A in the optimum fit curve of trigonometric function is found out according to fitting functionrWith phase angle αr, shown in following formula:
And then the functional relation of the electricity data of r-th of period acquisition of same acquisition device is obtained, shown in following formula:
g(tr)=Arsin(ωrtr+αr)
Step 1.3 repeats step 1.2, obtains the piecewise fitting function that data are acquired under same acquisition device different frequency,
g(t1), g (t2) ..., g (tm), as shown in Figure 3；
Step 2 determines that power grid needs to be sought the same profile data at moment；
Step 2.1 determines a time reference point, and find out different frequency on a timeline similarly hereinafter a time point when
Between；
If with frequency f1Take t in the data period a little1For the benchmark time, then with frequency frThe correspondence time a little is taken in period
Shown in the following formula of point:
Step 2.2, the time that step 2.1 is found out are brought by the expression formula of the obtained piecewise fitting function of step 1.3
In, the corresponding data value at section time point of seeking common ground, shown in following formula:
g(tr)=Arsin(ωrtr+αr)
Step 2.3 repeats step 2.2, calculates r=1, g (t when 2,3 ..., mr), and then find out the number of all same sections
According to；
Step 3: the data of all same sections found out are formed into same section number as shown in Figure 4 in data display platform
According to.
Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
Present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: it still may be used
To modify to technical solution documented by previous embodiment, or some or all of the technical features are equal
Replacement；And these are modified or replaceed, model defined by the claims in the present invention that it does not separate the essence of the corresponding technical solution
It encloses.
Claims (4)
1. a kind of AC sampling is the same as profile data generation method, it is characterised in that: the following steps are included:
Step 1, the real time electrical quantity data that power grid is acquired using acquisition device different in power grid, and same acquisition device is acquired
Electricity data be fitted on different tones；
Step 2, the time at find out different frequency on a timeline similarly hereinafter time point, determine that power grid needs to be asked the same disconnected of moment
Face data；
The data of all same sections found out are formed same profile data in data display platform by step 3.
2. a kind of AC sampling according to claim 1 is the same as profile data generation method, it is characterised in that: described in step 1
The electricity data of same acquisition device acquisition is fitted on different tones method particularly includes:
Step 1.1 acquires different frequency (f using the acquisition device in power grid1, f2, f3... ... fm) under power grid real time electrical quantity number
According to, and data collected are classified according to different frequencies；Obtain the real time electrical quantity data of same acquisition device acquisition
Are as follows: [(t1,1, y1,1)、(t1,2, y1,2)、……(t1, n, y1, n)]、[(t2,1, y2,1)、(t2,2, y2,2)、……(t2, n,
y2, n)]、……[(tR, 1, yR, 1)……(tR, i, yR, i)……(tR, n, yR, n)]……[(tM-1,1, yM-1,1)、(tM-1,2,
yM-1,2)、……(tM-1, n, yM-1, n)]、[(tM, 1, yMm, 1)、(tM, 2, yMm, 2)、……(tM, n, yM, n)]；
Wherein, tR, iFor frequency frWhen, the time of i-th of electricity data of acquisition；yR, iFor frequency frWhen, i-th of electricity of acquisition
Data, i=1,2 ..., n, n is the power grid real time electrical quantity data of same acquisition device acquisition in power grid, r=1,2 ..., m, m
For different total number of frequencies；
Power grid real time electrical quantity data [(t under step 1.2, the same frequency for acquiring acquisition device same in power gridR, 1,
yR, 1)……(tR, i, yR, i)……(tR, n, yR, n)] be fitted with three parametric sinusoidal wave profile fitting algorithms；
Step 1.3 repeats step 1.2, obtains the piecewise fitting function that data are acquired under same acquisition device different frequency, g
(t1), g (t2) ..., g (tm)。
3. a kind of AC sampling according to claim 2 is the same as profile data generation method, it is characterised in that: the rapid step
1.2 method particularly includes:
Step 1.2.1, seek common ground an acquisition device frequency be frWhen sampling period；
The sampling rate of known acquisition device is vr, the sampling interval is Δ tr, number of samples n, then the angular frequency in each sampling period
Rate is
Step 1.2.2, it seeks common ground the matched curve of electricity data that an acquisition device acquires under same sample frequency；
The data sequence that same acquisition device acquires under same sample frequency is (tR, 1, yR, 1)……(tR, i, yR, i)……
(tR, n, yR, n), then the sinusoidal discrete form of the data acquired are as follows:
yR, i=Brsin(ωr tR, i)+Crcos(ωr tR, i) (2)
Wherein, BrAnd CrFor equal coefficient；
Choose BrAnd Cr, keep residual sum of squares (RSS) shown in following formula minimum:
Coefficient B at this timer=Br0And Cr0Least square fitting value for the electricity data acquired under same frequency；
Step 1.2.3, the described selection BrAnd Cr, keep residual sum of squares (RSS) the smallest method particularly includes:
Construct following matrix:
It is then matrix form by residual sum of squares (RSS) simplification of a formula, shown in following formula:
WhenWhen minimum, unknown θ is obtainedrLeast square solutionShown in following formula:
Shown in the following formula of the fitting function of the electricity data then acquired under same frequency:
The amplitude A in the optimum fit curve of trigonometric function is found out according to fitting functionrWith phase angle αr, shown in following formula:
And then the functional relation of the electricity data of r-th of period acquisition of same acquisition device is obtained, shown in following formula:
g(tr)=Arsin(ωrtr+αr)。
4. a kind of AC sampling according to claim 3 is the same as profile data generation method, it is characterised in that: the rapid step 2
Method particularly includes:
Step 2.1 determines a time reference point, and the time at find out different frequency on a timeline similarly hereinafter time point；
If with frequency f1Take t in the data period a little1For the benchmark time, then with frequency frCorrespondence time point a little is taken in period such as
Shown in lower formula:
Step 2.2, the time that step 2.1 is found out are brought into the expression formula by the obtained piecewise fitting function of step 1.3, are asked
With the corresponding data value at section time point, shown in following formula:
g(tr)=Arsin(ωrtr+αr)
Step 2.3 repeats step 2.2, calculates r=1, g (t when 2,3 ..., mr), and then find out the data of all same sections.
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| CN111144705A (en) * | 2019-12-05 | 2020-05-12 | 国网辽宁省电力有限公司锦州供电公司 | Whole-network same-section data processing method based on information acquisition with time scale |
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